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Resolving Ambiguities to Create a Natural Sketching Environment

Explore how to improve accuracy while allowing creative freedom in sketch interpretation. Christine Alvarado presents models and methods to resolve ambiguities efficiently, enhancing interaction between sketch designers and observers. Learn about the three stages of interpretation - Recognition, Reasoning, and Resolution, and discover the impact of contextual knowledge and user feedback on interpretation quality. Overcome limitations of bottom-up recognition by applying structured context and balancing heuristic weights based on preferences for simpler interpretations and contiguous strokes.

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Resolving Ambiguities to Create a Natural Sketching Environment

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  1. Resolving Ambiguities to Create a Natural Sketching Environment Christine Alvarado and Randall Davis MIT AI Laboratory

  2. Our Model • The Designer Sketches with Pen and Paper • The Observer Interprets the Sketch • The Observer and Designer Interact Christine Alvarado

  3. Sketch Interpretation Christine Alvarado

  4. Accuracy vs. Freedom Free Sketch ASSIST Single Stroke Recognition Recognition Difficulty “Put That There” Menu Drawing Freedom Christine Alvarado

  5. Smarter interpretation increases accuracy Better interaction design increases perceived freedom Accuracy and Freedom Christine Alvarado

  6. Levels of Interpretation Fluid Interpretation Commitment to an Interpretation Resolving Ambiguities Christine Alvarado

  7. 3 Stages of Interpretation • Recognition • Reasoning • Resolution Christine Alvarado

  8. Generate All Possible Interpretations: Circle Circular Body Pin Joint Recognition Christine Alvarado

  9. Temporal Evidence Simpler Is Better Context Domain Knowledge User Feedback Reasoning: Heuristics Christine Alvarado

  10. Temporal Evidence Simpler Is Better Context Domain Knowledge User Feedback Reasoning: Heuristics Christine Alvarado

  11. Temporal Evidence Simpler Is Better Context Domain Knowledge User Feedback Reasoning: Heuristics 1 arrow or 3 rods? Christine Alvarado

  12. Reasoning: Heuristics • Temporal Evidence • Simpler Is Better • Context • Domain Knowledge • User Feedback Christine Alvarado

  13. Reasoning: Heuristics • Temporal Evidence • Simpler Is Better • Context • Domain Knowledge • User Feedback Christine Alvarado

  14. Reasoning: Heuristics • Temporal Evidence • Simpler Is Better • Context • Domain Knowledge • User Feedback Christine Alvarado

  15. Reasoning: Heuristics • Temporal Evidence • Simpler Is Better • Context • Domain Knowledge • User Feedback Total Score Christine Alvarado

  16. Resolution Christine Alvarado

  17. Resolution 0 6 3 Christine Alvarado

  18. Resolution 0 6 3 Christine Alvarado

  19. Resolution 0 0 10 10 5 5 Christine Alvarado

  20. Resolution 0 0 10 10 5 5 Christine Alvarado

  21. Resolution 0 0 0 0 6 6 6 6 3 3 3 3 Christine Alvarado 10

  22. Resolution 0 0 0 0 6 6 6 6 3 3 3 3 Christine Alvarado 10

  23. Resolution 0 0 0 0 0 6 6 6 6 6 3 3 3 3 3 8 Christine Alvarado 10

  24. Resolution 0 0 0 0 0 6 6 6 6 6 3 3 3 3 3 8 Christine Alvarado 10

  25. Resolution 0 0 0 0 0 6 6 6 6 6 3 3 3 3 3 8 Christine Alvarado 10

  26. ??? line line line Limitations • Relies heavily on bottom-up recognition Line + Line + Line + ???  ??? Christine Alvarado

  27. Limitations • Relies heavily on bottom-up recognition • Heuristics all weighted equally H1: Prefer interpretations resulting in fewer objects H2: Prefer objects drawn with contiguous strokes Christine Alvarado

  28. Limitations • Relies heavily on bottom-up recognition • Heuristics all weighted equally H1: Prefer interpretations resulting in fewer objects H2: Prefer objects drawn with contiguous strokes Christine Alvarado

  29. Limitations • Relies heavily on bottom-up recognition • Heuristics all weighted equally H1: Prefer interpretations resulting in fewer objects H2: Prefer objects drawn with contiguous strokes Christine Alvarado

  30. Structured Application of Context • Blackboard recognition architecture • Heuristics applied probabilistically Christine Alvarado

  31. Body(b1) Polygon(p1) Connects(l5, l6) Connects(l6, l7) Line(l6) Recognition Blackboard Blackboard Forces push bodies Force(f1) Sketch Arrow(a1) Connects(l1, l2) Connects(l4, l5) Connects(l1, l2) Connects(l7, l4) Connects(l1, l2) Line(l1) Line(l2) Line(l3) Line(l4) Line(l5) Line(l7) Stroke(s1) Stroke(s2) Stroke(s3) Stroke(s4) Stroke(s5) Stroke(s6) Stroke(s7) Christine Alvarado

  32. Bayesian Network Structure Heuristics influence prior … Property1 Property2 Line1 Line2 Line3 … Low-level information influences recognition Christine Alvarado

  33. Related Work • Gross and Do (1996) • Landay and Meyers (2001) • Stahovich (1998) • Matsakis (1999) Christine Alvarado

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